• DocumentCode
    3207282
  • Title

    Genetic Algorithm approach for sinhala speech recognition

  • Author

    Priyadarshani, P.G.N. ; Dias, N.G.J. ; Punchihewa, Amal

  • Author_Institution
    Dept. of Stat. & Comput. Sci., Univ. of Kelaniya, Kelaniya, Sri Lanka
  • fYear
    2012
  • fDate
    5-8 Aug. 2012
  • Firstpage
    896
  • Lastpage
    899
  • Abstract
    For centuries, researchers around the world have attempted to develop a natural interface between human and computer that enables the computer to speak and understand the natural language as the humans do. Even speech recognition systems for some recognized languages have been developed to some extent; still people prefer to work with their native language. On the other hand, speaker dependability has been a major issue in many cases and majority of users prefer if the recognizer is independent of speaker because in a speaker dependent platform, each user has to undergo training phase as the recognizer does not keep reference templates for each potential user. In this research, Genetic Algorithm (GA) was successfully applied with Mel Frequency Cepstral Coefficients (MFCC) to identify separately pronounced Sinhala words in both speaker independent and speaker dependent platforms.
  • Keywords
    genetic algorithms; natural languages; speech recognition; GA; MFCC; Sinhala speech recognition; genetic algorithm approach; mel frequency cepstral coefficients; natural language; Biological cells; Genetic algorithms; Mel frequency cepstral coefficient; Sociology; Speech; Speech recognition; Statistics; HCI; MFCC; crossover; genetic algorithm; mutation; selection; threshold;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (MWSCAS), 2012 IEEE 55th International Midwest Symposium on
  • Conference_Location
    Boise, ID
  • ISSN
    1548-3746
  • Print_ISBN
    978-1-4673-2526-4
  • Electronic_ISBN
    1548-3746
  • Type

    conf

  • DOI
    10.1109/MWSCAS.2012.6292165
  • Filename
    6292165